The presence of DDT and derivatives in the food web of freshwater ecosystems of Rangsit agricultural area, Pathum Thani Province, Thailand were investigated from June 2004 to May 2007. By using gas chromatography (GC) with micro electron capture detector (mu ECD), DDT and derivatives in water, sediment, and fifteen indicator species i.e., 2 producers; Eichhornia crassipes and plankton (phyto- and zoo- plankton), an herbivore; Trichogaster microlepis (3) 3 omnivores; Trichogaster trichopterus, Oreochromis niloticus, and Puntius gonionotus, 6 carnivores; Channa striatus, Oxyeleotris marmoratus, Macrognathus siamensis, Parambassis siamensis, Anabas testudineus, and Pristolepis fasciatus, and 3 detritivores; Macrobrachium lanchesteri, Pomacea sp., and Filopaludina mertensi were measured. Results show low concentration levels (part per billion) of DDT & derivatives in each food web compartment i.e. water, sediment, aquatic plant, plankton, fish, and invertebrates. Magnification patterns, i.e. bioconcentration, bioaccumulation, and biomagnification, based on habitat and foraging behavior of selected freshwater species indicates that DDT & derivatives can accumulate and be magnified through the food chain from the lowest up to the highest trophic level. Therefore, the presence of residues and the evidence of magnification patterns can be observed as ecological indicators for evaluating ecological health risk.
Indicators of resource use such as material and energy flow accounts, emission data and the ecological footprint inform societies about their performance by evaluating resource use efficiency and the effectiveness of sustainability policies. The human appropriation of net primary production (HANPP) is an indicator of land-use intensity on each nation's territory used in research as well as in environmental reports. 'Embodied HANPP' (eHANPP) measures the HANPP anywhere on earth resulting from a nation's domestic biomass consumption. The objectives of this article are (i) to study the relation between eHANPP and other resource use indicators and (ii) to analyse socioeconomic and natural determinants of global eHANPP patterns in the year 2000. We discuss a statistical analysis of >140 countries aiming to better understand these relationships. We found that indicators of material and energy throughput, fossil-energy related CO2 emissions as well as the ecological footprint are highly correlated with each other as well as with GDP, while eHANPP is neither correlated with other resource use indicators nor with GDP, despite a strong correlation between final biomass consumption and GDP. This can be explained by improvements in agricultural efficiency associated with GDP growth. Only about half of the variation in eHANPP can be explained by differences in national land-use systems, suggesting a considerable influence of trade on eHANPP patterns. eHANPP related with biomass trade can largely be explained by differences in natural endowment, in particular the availability of productive area. We conclude that eHANPP can deliver important complimentary information to indicators that primarily monitor socioeconomic metabolism.
The per capita ecological footprint (EF) is one of the most-widely recognized measures of environmental sustainability. It seeks to quantify the Earth's biological capacity required to support human activity. This study presents a Bayesian approach to predict the EF of 140 nations. By formulating the linear regression in a probabilistic framework, a Bayesian linear regression model is derived, and a specific simulation method, i.e., Markov Chain Monte Carlo (MCMC), is utilized to estimate the model parameters. Bayesian MCMC methods allow a richer and more complete representation of complex EF data. It also provides a computationally attractive and straightforward method to develop a full and complete description of the inherent uncertainty in parameters, quantiles and performance metrics. Results show that the per capita EF is positively influenced by the nation's world system position (WSP) and its urbanization level. The distribution of income, as measured by the Gini coefficient, was found to be negatively related to per capita EF.
Landscape networks and ecosystems worldwide are undergoing changes that may impact in different ways relevant ecological processes such as gene flow, pollination, or wildlife dispersal. A myriad of indices have been developed to characterize landscape patterns, but not all of them are equally suited to evaluate temporal changes in landscape connectivity as is increasingly needed for biodiversity monitoring and operational indicator delivery. Relevant advancements in this direction have been recently proposed based on graph theoretical methods to analyze landscape network connectivity and on the measurement of habitat availability at the landscape scale. Building from these developments, we modify a recent index and present the equivalent connected area (ECA) index, defined as the size of a single patch (maximally connected) that would provide the same probability of connectivity than the actual habitat pattern in the landscape. The temporal changes in ECA can be directly compared with the changes in total habitat area. This allows for additional and straightforward insights on the degree to which the gains or losses in habitat amount can be beneficial or deleterious by affecting landscape elements that uphold connectivity in a wider landscape context. We provide a demonstrative example of application and interpretation of this index and approach to monitor changes in functional landscape connectivity. We focus on the trends in European forests at the province level in the period 1990–2000 from Corine land cover data, considering both changes in the forest spatial pattern and in the average permeability of the landscape matrix. The degree of connectivity was rather stable over most of the study area, with a slight overall increase in forest connectivity in Europe. However, a few countries and regions concentrated remarkably high changes in the analyzed period, particularly those with a low forest cover. The species traits also affected the responses to landscape pattern changes, which were more prominent for those species with limited dispersal abilities. We conclude discussing the potential of this approach for consistent indicator delivery, as well as the limitations and possibilities of application to a variety of situations, for which the required quantitative tools are freely available as open source projects.
A simple and reproducible algal tissue extraction protocol and a total antioxidant, radical cation decolourisation spectroscopic assay has been developed. This was applied to ascertain the potential for using algae and their stress responses as biological and biochemical indicators of environmental impacts in urban ponds. Total antioxidant and soluble protein profiles were constructed for the green alga Cladophora glomerata, which was seasonally sampled, from three sustainable urban drainage systems (SUDS) ponds located in an industrial and residential development created on a former Greenfield area in Fife, Scotland. Algal antioxidant profiles were impacted by a combination of lifecycle and pond structural parameters, including: seasonal sampling time, pond site and pond structure (e.g. inlet, outlet). The assay, as applied to algae as primary producer–indicator organisms is recommended for use in aquatic environmental monitoring programmes, which have a requirement to maintain the health status of disturbed aquatic urban ecosystems.
In the course of evaluating the progress in implementing Agenda 21 [Results of the World Conference on Environment and Development: Agenda 21, UNCED United Nations Conference on Environment and Development, Rio de Janeiro, United Nations, New York] the “Commission on Sustainable Development” began developing a set of indicators of sustainable development. The first version was finalised in 1996 with the suggestion of 134 indicators [Indicators of Sustainable Development, Framework and Methodologies, United Nations, New York] and put to a field test, resulting in a final version published in 2001 [Indicators of Sustainable Development: Guidelines and Methodologies, United Nations, New York]. In both versions, the indicators are divided up into for issue areas: economic, environmental, social, and institutional. The further conceptual separation into driving force, state, and response indicators was given up in the final version.
Economic cost–benefit appraisal (and its sub-set cost-effectiveness) of ecosystem conservation and/or pollution abatement strategies have proved to be powerful decision-making aids. But the monetary economic valuation of ecosystem goods and services (gains and losses) can only provide a good indication of social welfare impacts under certain conditions and in selective contexts. The values derived through this appraisal process will, for a number of measures, be underestimates of the full total system value [Turner, R.K., Paavola, J., Cooper, P. Farber, S., Jessamy, V., Georgiou, S., 2003. Valuing nature: lessons learned and future research directions. Ecol. Econ. 46, 493–510]. The economic analysis is best suited to assessing the value of ‘marginal’ gains and losses in ecosystem goods/services and not the total destruction of whole systems (including life support systems, the value of which is not commensurate with monetary values and/or is infinitely high). In this study economic costs and what we call ‘ecological risk’ analysis are used to appraise the implementation costs and ecological benefits of selected measures for combating eutrophication. Ecological risk is expressed in terms of ecosystem integrity and resilience. The paper presents three regional case studies dealing with the issue of nutrient emission reduction to the southern North Sea, namely the catchments/estuaries of the Humber (UK), the Rhine (Germany and The Netherlands) and the Elbe (Czech Republic and Germany). On the basis of these comparative regional examples, wider implications in the light of international management of the North Sea are presented.
Abundance-weighted averages of diatom indicator values for pH, salinity, organic nitrogen availability, oxygen saturation, saprobity and trophic status according to van Dam et al. [Neth. J. Aquat. Ecol. 28 (1994) 117] were calculated for surface sediment and epiphytic diatom assemblages in 186 standing waters distributed throughout Flanders, Belgium, and tested against environmental variables measured in the water column, covering water chemistry, trophic status and organic load. With exception of the pH indication, most scores related rather poorly to variables which they are assumed to reflect and correlated even more strongly to non-target variables. For instance, the trophic indication provided a measure of pH and base status rather than of nutrient levels or phytoplankton productivity. Relations to measured variables differed according to the pH regime. Correction for uneven distribution of indicator values in the species pool usually yielded little improvement and was detrimental in some cases. Compared to epiphyton, weighted averages of species indicator values derived from sediment assemblages tended to be higher in water bodies yielding the most elevated indication scores. Except for the pH and salinity indication, differences between weighted averages pertaining to these different habitats were often considerable. Limitations to the use of abundance-weighted averages of diatom indicator values for environmental monitoring and assessment of lentic waters are discussed.
Previously, standardized snap-shot models of the Southern Benguela (1980–1989), Southern Humboldt (1992) and Southern Catalan Sea (1994) ecosystems were examined and found to facilitate assessment of ecosystem characteristics related to the gradient in exploitation status of the ecosystems; highest level of exploitation in the South Catalan Sea (North-western Mediterranean), high in the Southern Humboldt and lower in the Southern Benguela. Subsequently, these models were calibrated and fitted using available catch, fishing effort/mortality and abundance data series and incorporated environmental and internal drivers. This study furthers the previous comparative analyses by comparing changes in ecosystem structure using a selection of ecosystem indicators from the calibrated models and assessing how these indicators change over time in these three contrasting ecosystems. Indicators examined include community turnover rates (production/biomass), trophic level of landings and the community, biodiversity indicators, ratios of predatory/forage fish and pelagic/demersal fish biomass, catch ratios, and network analysis indicators. Using the set of model-derived indicators, the three ecosystems were ranked in terms of exploitation level. This ranking was performed using the values of these indicators in recent years (ecosystem state) as well as their trends over time (ecosystem trend). The non-parametric Kruskal–Wallis and Median tests were used to test for significance of the difference between indicators from the three ecosystems in the last 5 years of the simulation to compare present ecosystem states. We compared the slope of the lineal trend and its significance between ecosystems using the generalized least-squares regression taking auto-correlation into consideration to analyse ecosystem trends. The indicators that capture better the high impacts of fishing prevalent in the Mediterranean and Humboldt ecosystems, and the more conservative exploitation of the Southern Benguela, are the fish/invertebrates biomass and catch ratio, the demersal/pelagic fish biomass and catch ratio (depending on the ecosystem and the fishery being developed), flows to detritus, and the mean trophic level of the community (when large, poorly quantified groups such as zooplankton and detritus are excluded). This study suggests that the best option for classifying ecosystems according to the impact of fishing is to consider a broad range of indicators to understand how and why an ecosystem is responding to particular environmental or fishing drivers (or more likely a combination of these). Our results highlight the importance of including indicators capturing trends over time as well as recent ecosystem states. We also identified 23 pairs of indicators that correlated similarly in the three ecosystems (they showed a significant correlation with same sign). Further comparisons may contribute towards generalization of this list, progressing towards a better understanding of the behaviour of ecological indicators.
In order to decide on measures to preserve and restore seagrasses and macroalgae, there is a need for identifying quantitative links between eutrophication pressure and vegetation response. This study compiles existing empirical relationships between eutrophication-related variables and responses measured in terms of distribution and abundance of seagrasses and macroalgae and analyses similarities and differences between responses in different ecosystems. The compilation includes 73 relationships originating from 38 publications from the period 1982 to 2007 and covering a wide range of ecosystems. Of the 73 relationships, 38 link vegetation responses significantly to eutrophication pressure as expressed by nutrient richness or water transparency, 18 link the responses to combinations of eutrophication pressure and ecosystem characteristics and 9 link the responses to ecosystem characteristics alone. The remaining relationships are either non-significant (3) or include no information on significance levels (5). The compilation demonstrates that seagrasses and macroalgae generally respond quantitatively to changes in eutrophication pressure by growing deeper, being more abundant and more widely distributed in clear waters with low nutrient concentration as compared to more turbid and nutrient-rich ecosystems. Vegetation in deeper waters shows the strongest response because it is most markedly affected by shading effects of eutrophication. This similarity in the patterns of response indicates a wide robustness and generality of the findings. However, the sensitivity of the vegetation to shading effects of eutrophication varies widely across ecosystems. We attribute this variability to additional eutrophication effects such as anoxic events, and ecosystem characteristics such as water residence time, sediment characteristics, or presence of grazers that may modify the response of the vegetation to a given eutrophication pressure. We encourage taking into account and quantifying such effects in order to improve the predictive power of future empirical relationships.
Ants are used as indicators of environmental change in disturbed landscapes, often without adequate understanding of their response to disturbance. Ant communities in the southeastern United States displayed a hump-backed species richness curve against an index of landscape disturbance. Forty sites at Fort Benning, in west-central Georgia, covered a spectrum of habitat disturbance (military training and fire) in upland forest. Sites disturbed by military training had fewer trees, less canopy cover, more bare ground, and warmer, more compact soils with shallower A-horizons. We sampled ground-dwelling ants with pitfall traps, and measured 15 habitat variables related to vegetation and soil. Ant species richness was greatest with a relative disturbance of 43%, but equitability was greatest with no disturbance. Ant abundance was greatest with a relative disturbance of 85%. High species richness at intermediate disturbance was associated with greater within-site spatial heterogeneity. Species richness was also associated with intermediate values of the normalized difference vegetation index (NDVI), a correlate of net primary productivity (NPP). Available NPP (the product of NDVI and the fraction of days that soil temperature exceeded 25 °C), however, was positively correlated with species richness, though not with ant abundance. Species richness was unrelated to soil texture, total ground cover, and fire frequency. Ant species richness and equitability are potential state indicators of the soil arthropod community. Moreover, equitability can be used to monitor ecosystem change.
We propose using future vascular plant abundances as indicators of future climate in a way analogous to the reconstruction of past environments by many palaeoecologists. To begin monitoring future short-term climate changes in the forests of Oregon and Washington, USA, we developed a set of transfer functions for a present-day calibration set consisting of climate parameters estimated, and species abundances measured, at 107 USDA Forest Service FIA (Forest Inventory and Analysis) Phase 3 plots. For each plot, we derived climate estimates from the Daymet model database, and we computed species abundance as quadrat frequency and subplot frequency. We submitted three climate variables (mean January temperature, MJAT; mean July temperature, MJUT; and mean annual precipitation transformed to natural logarithms, MANPt) to canonical correspondence analysis (CCA), and verified their importances in structuring the species frequency data. Weighted averaging-partial least squares regression (WA-PLS) provided the means for calculating six transfer functions. In all cases, based on performance statistics generated by leave-one-out cross-validation, we identified two-component WA-PLS models as the most desirable. The predictive abilities of our transfer functions are comparable to, or better than, those reported in the literature, probably due both data quality and statistical considerations. However, model overfitting as a result of spatial autocorrelation remains a possibility. The large errors associated with our MJAT transfer functions connote that even the highest amount of change in mean January temperature predicted for Oregon and Washington for 2010–2039 would be indistinguishable from current conditions. The higher predictions indicate that our MJAT transfer functions may be able to track climate changes by the 2040s. Our MJUT transfer functions can detect change in mean July temperature under the highest projection for 2010–2039. Our MANPt transfer functions will be of limited use until the 2070s, given the predictions of only slight changes in mean annual precipitation during the early part of the twenty-first century. Our MJAT and MANPt transfer functions may prove useful at the present time to verify relative climatic stability. Because the predicted climate values sometimes deviate substantially from the observed values for individual plots, our transfer functions are appropriate for monitoring climatic trends over the entire Pacific Northwest or large regions within it, not for assessing climate change at individual plots.
Safe water quality criteria on the load and types of microbial populations are important for human use from fishery, tourism and navigational viewpoints. To understand the variations in sewage pollution indicator and certain human pathogenic bacteria, data collected from various locations along central west coast of India during 2002–2007 were analyzed. Water and sediment samples were examined for total viable counts (TVC), pollution indicator bacteria (total coliforms – TC, fecal coliforms – FC and Escherichia coli – EC) and potential pathogens (Vibrio cholerae – VC, Shigella – SH, and Salmonella spp. – SA). In both Mandovi and Zuari estuaries, where fishing and tourist-related activities are sizable and long-term data collection was regular, we observed high counts of TC, FC, VC, SH and SA in particular during monsoon due to increased land runoff. Further, the abundance of TC and FC has increased significantly over the years in the water column to much above either USEPA or India permissible limits. The concentrations of Vibrio cholerae, and Shigella correlated with those of coliforms. Pathogenic bacteria were detected even 20 km and/or 25 km offshore mainly due to dumping of raw or improperly treated sewage effluents either from land, fishing trawlers and/or ships in the anchorage. Higher concentrations of fecal coliforms and pathogenic bacteria in neretic waters signify threats to environmental and human health.
Different approaches for the assessment of biodiversity by means of remote sensing were developed over the last decades. A new approach, based on the spectral variation hypothesis, proposes that the spectral heterogeneity of a remotely sensed image is correlated with landscape structure and complexity which also reflects habitat heterogeneity which itself is known to enhance species diversity. In this context, previous studies only applied species richness as a measure of diversity. The aim of this paper was to analyze the relationship of richness and abundance-based diversity measures with spectral variability and compare the results at two scales. At three different test sites in Central Namibia, measures of vascular plant diversity was sampled at two scales – 100 m2 and 1000 m2. Hyperspectral remote sensing data were collected for the study sites and spectral variability, was calculated at plot level. Ordinary least square regression was used to test the relationship between species richness and the abundance-based Shannon Index and spectral variability. We found that Shannon Index permanently achieved better results at all test sites especially at 1000 m2, Even when all sites where pooled together, Shannon Index was still significantly related with spectral variability at 1000 m2. We suggest incorporating abundance-based diversity measures in studies of relationships between ecological and spectral variability. The contribution made by the high spectral and spatial resolution of the hyperspectral sensor is discussed.
Random deviations from the perfect symmetry of normally bilaterally symmetrical characters exist during individual development as a result of various environmental conditions. Fluctuating asymmetry (FA) is often used as a measurement of developmental instability, and within-environmental variation (CVe) is also considered as an indicator of developmental deviations. These two parameters may indicate the quality of the environmental habitat of organisms. For herbivore insects, such as aphids, any change in their host plants conditions is important and directly affects their development. The presented investigation revealed that both Lead (Pb) and Copper (Cu) accumulation in different host plants resulted in a significant amount of deviations from bilateral symmetry in cabbage aphid (Brevicoryne brassicae). Cabbage aphid populations showed higher FA and CVe on heavy metal accumulated cabbage and radish than on non-contaminated cabbage and radish plants. However, the pattern between developmental instability and fitness measurements was inconsistent. Thus, this study does not support the hypothesis that asymmetry is a valuable bioindicator of developmental instability.
The impact of Candiota coal-fired thermal power plant on air quality was evaluated during two years by means of passive biomonitoring. The monitoring consisted of the quarterly collection of leaf samples of Baccharis dracunculifolia, Elephantopus mollis, Eryngium horridum, Paspalum notatum and Piptochaetium montevidense or the shoot of Baccharis trimera at five sites located in the area around the power plant. The element load of these plants was used as indicator for atmospheric pollution. In the samples collected, sulphur and heavy metal cadmium contents were measured. Among the species evaluated, E. mollis presented the highest potential to accumulate metal, followed by B. trimera. The Aeroporto and AFUCAN sampling sites, located in the prevailing wind directions, presented the highest level of metal contamination.
In Germany, ectohydrical mosses were used as passive bioindicators for metal accumulation in terrestrial ecosystems in 1990, 1995 and 2000. The data quality, empirical aspects of the moss-monitoring campaigns, like the monitoring net design, moss-sampling as well as chemical analysis are described. By using the site-specific sample data on the metal accumulation, spatially valid information without geographical gaps is calculated by applying geostatistics for the whole territory of Germany. Furthermore, the metal-specific data are aggregated to statistical indices. Two aggregation procedures are used. The cluster analytical approach results in regional categories of accumulation spectra. It allows for an investigation if the emission structures remain the same over time or if they change from one campaign to the following one. The approach based on percentile statistics provides ranked or ordinal indices, which illustrate both spatial and temporal trends of metal accumulation. The respective maps show the spatial patterns of reduced metal accumulation throughout the monitoring campaigns.
The assessment of landscape spatial patterns is a key issue in landscape management. Landscape pattern indices (LPIs) are tools appropriate for analyzing landscape spatial patterns. LPIs are often derived from raster land cover maps that are extracted from remotely sensed data through hard classification. However, pixel-based hard classification methods suffer from the mixed pixel problem (in which pixels contain more than one land cover class), making for inaccurate classification maps and LPIs. In addition, LPIs generated by hard classification methods are characterized by grain sizes (the sampling unit sizes) that limit the derived landscape pattern to a certain scale. Sub-pixel mapping (SPM) models can enable fine-scale estimation of the spatial patterns of land cover classes without requiring additional data; hence, this is an appropriate downscaling method for land cover mapping. The fraction images generated by soft classification estimate the area proportion of each land cover class within each pixel, and using these images as input enables SPM models to alleviate the mixed pixel problem. At the same time, by transforming fraction images into a finer-scaled hard classification map, SPM models can minimize the influence of grain size on LPIs calculation. In this research, simulated landscape thematic patterns that can provide different landscape spatial patterns, eight commonly used LPIs and a SPM model that maximizes the spatial dependence between neighbouring sub-pixels were applied to assess the efficiency of deriving LPIs from sub-pixel model maps. Results showed that the SPM model can more precisely characterize landscape patterns than hard classification methods can. Landscape fragmentation, class abundance, the uncertainty in SPM, and the spatial resolution of the remotely sensed data influenced LPIs derived from sub-pixel maps. The largest patch index, landscape division, and patch cohesion derived from remotely sensed data with different spatial resolutions through the SPM model were suitable for inter-comparison, whereas the patch density, mean patch area, edge density, landscape shape index, and area-weighted mean shape index derived from the sub-pixel maps were sensitive to the spatial resolution of the remotely sensed data.
Limited stream chemistry and macroinvertebrate data indicate that acidic deposition has adversely affected benthic macroinvertebrate assemblages in numerous headwater streams of the western Adirondack Mountains of New York. No studies, however, have quantified the effects that acidic deposition and acidification may have had on resident fish and macroinvertebrate communities in streams of the region. As part of the Western Adirondack Stream Survey, water chemistry from 200 streams was sampled five times and macroinvertebrate communities were surveyed once from a subset of 36 streams in the Oswegatchie and Black River Basins during 2003–2005 and evaluated to: (a) document the effects that chronic and episodic acidification have on macroinvertebrate communities across the region, (b) define the relations between acidification and the health of affected species assemblages, and (c) assess indicators and thresholds of biological effects. Concentrations of inorganic Al in 66% of the 200 streams periodically reached concentrations toxic to acid-tolerant biota. A new acid biological assessment profile (acidBAP) index for macroinvertebrates, derived from percent mayfly richness and percent acid-tolerant taxa, was strongly correlated (R2 values range from 0.58 to 0.76) with concentrations of inorganic Al, pH, ANC, and base cation surplus (BCS). The BCS and acidBAP index helped remove confounding influences of natural organic acidity and to redefine acidification-effect thresholds and biological-impact categories. AcidBAP scores indicated that macroinvertebrate communities were moderately or severely impacted by acidification in 44–56% of 36 study streams, however, additional data from randomly selected streams is needed to accurately estimate the true percentage of streams in which macroinvertebrate communities are adversely affected in this, or other, regions. As biologically relevant measures of impacts caused by acidification, both BCS and acidBAP may be useful indicators of ecosystem effects and potential recovery at the local and regional scale.
The development of ecological indicators for actively monitoring an ecosystem at a high resolution in scale, space and time is a challenge of primary interest. In this context, measures of structural complexity derived from close-range repeat photography may form a part of the solution. Moreover, recent mathematical tools, such as recurrence plots and recurrence quantification analysis (RP-RQA), are becoming accessible for characterizing the multivariate dynamics of natural systems given short, stochastic and non-stationary series. In this study, a total of 9360 grey-level digital images were recorded on a weekly basis across 72 sites in an old-growth forest ecosystem and analyzed for structural complexity. Structural complexity was assessed using an information theoretic measure (mean information gain). The effect of the scene scale on the observed dynamics was verified across a gradient of forest descriptors and light habitats. Multiscale dynamics responded nonlinearly to changes in scene scale, whereas seasonal trends in structural complexity showed a range of deterministic and stochastic behaviours. The determinism of multiscale time-series was related to sapling density, tree cover, and tree species richness. The sensitivity and flexibility of the RP-RQA approach applied to proxy measures of structural complexity in digital images forms an efficient methodology which might be used for actively monitoring forest ecosystems. This field study is one of the first to demonstrate that old-growth forest ecosystems behave like complex systems exhibiting nonlinear vegetation structure and dynamics across scales.
Coarse and fine woody materials (CWD and FWD) are substantial forest ecosystem carbon (C) stocks. There is a lack of understanding how these detritus C stocks may respond to climate change. This study used a nation-wide inventory of CWD and FWD in the United States to examine how these C stocks vary by latitude. Results indicate that the highest CWD and FWD C stocks are found in forests with the highest latitude, while conversely the lowest C stocks are found in the most southerly forests. CWD and FWD respond differently to changes in latitude with CWD C stocks decreasing more rapidly as latitude decreased. If latitude can be broadly assumed to indicate temperature and potential rate of detrital decay, it may be postulated that CWD C stocks may be at the highest risk of becoming a net C source if temperatures increase. The latitude at which CWD and FWD C stocks roughly equal each other (equilibrium point) may serve as an indicator of changes in C stock equilibrium under a global warming scenario. Given the complex relationships between detrital C stocks, biomass production/decay, and climatic variables, further research is suggested to refine this study's indicator.
Diatoms are widely used in the biological monitoring of streams because they are strong responders to environmental change, but dispersal and spatial factors can play important and potentially confounding roles in the presence, absence, and abundance of species along with characterizing species–environment relationships. To examine how spatial factors affect diatom community structure and biomonitoring, multiple scales were sampled including the Western Allegheny Plateau (n = 58), Leading Creek watershed (n = 18), and the adjacent Shade River watershed (n = 21) in southeast Ohio. Partitioning of spatial, environmental, and spatially-structured environmental variation was conducted on diatom assemblages and on diatom metrics used in biomonitoring. At the regional scale, diatom assemblages and metrics had strong relationships with agricultural (e.g., significant correlations with nutrients, conductivity, and pasture/row crops in the watershed) and alkalinity gradients. Diatom assemblages and metrics in both watersheds were strongly associated with acid mine drainage (AMD) impacts, and when spatial factors were set as covariables in CCAs, relationships with AMD gradients became even stronger, indicating the need to consider how spatial factors could reduce the strength of diatom-environment relationships. Metrics calculated at all scales had very little variation explained exclusively by spatial factors, likely because multiple species are combined into a simplified metric that reduces the effects of species dispersal. Local environmental variables accounted for 57, 42, and 42% of the total variation explained (TVE), and spatial variables accounted for 28, 31, and 37% of the TVE in the regional, Leading Creek, and Shade River datasets, respectively. The amounts of variation in diatom assemblages explained solely by spatial factors at these scales were substantial and similar to what has been reported at continental, national, and large regional (Level I Omernik ecoregions) scales (approximately 1/3 of TVE). Although amounts of variation explained are similar across scales, processes underlying the spatial structure likely differ. In addition to describing ecological patterns, recognizing the potential influence of spatial factors could improve the identification and management of environmental problems at a range of scales, as well as aid in the development of new research questions and hypotheses aimed at exploring factors that could explain portions of the spatially explicit variation.
This paper presents for 16 typical forest types across Europe a standard carbon sequestration profile. The study was carried out with the model CO2FIX which was parameterised with local yield table data and additional required parameters. CO2FIX quantifies the carbon of the forest ecosystem–soil–wood products chain at the stand level. To avoid misleading results annual net sequestration rates are not presented here, because these strongly fluctuate in time. Therefore, only its advancing mean is presented as a more reliable indicator. This avoids a great deal of uncertainty for policy makers. The variation between forest types is large, but mean sequestration rates mostly peak after some 38 years (with a net source lasting up to 15 years after afforestation) at an average value of 2.98 Mg C ha−1 per year (ranging between forest types from 4.1 to 1.15). After 200 years, the net sequestration rate saturates to a value of 0.8 Mg C ha−1 per year (ranging from 1.4 to 0.13). The long-term mean carbon stock in tree biomass and products amounts on average to 114 Mg C ha−1 (ranging from 52 to 196).
Investigations into interactions between suspended bivalve farms and the marine environment generally focus on effects to the seafloor beneath farms. This is appropriate in situations where the level of development will be determined by the ability of the growing environment to absorb waste products, such as in the case for finfish culture operations. By contrast, sea-based suspended bivalve culture development is more often controlled by the ability of the water-column environment to supply particulate food material. Therefore, there is a need to develop methodologies and frameworks for assessing the ‘scope for growth’ of bivalve culture, and the level of environmental interactions associated with particular development levels. The work presented here details a set of functional performance indicators that can be used to assess the level of interactions between the culture and the water-column growing environment, and also the farmed biomass with respect to carrying capacity milestones.
This paper reports on a part of PRISMA project, funded by the Italian Ministry of Education, University and Research (M.U.R.S.T.), involving the biomonitoring of fish populations in two different Adriatic Sea sites by using some integrated descriptors at organismic level (skeletal anomalies and meristic count variation). Given the scarcity of up-to-date data on biology, physical and chemical oceanography, and environmental geophysics, as well on the degree of pollution of this Sea, the goal of the project was to contribute at enhancing the knowledge on environmental biology of Adriatic Sea. In particular, this part of the project analyzed different samplings of some mullets species for the presence of skeletal malformations under the hypothesis that stressed environment should induce alteration in skeletal development pattern in fish, as indicated by many authors. So, the investigation on mullets skeletal structures was utilized to monitor two different Adriatic Sea sites, where exhaustive information (chemical analysis of water and sediment, i.e.) on environmental conditions lack.
The assessment of agricultural performance in the last decades has been forced to move away from a single criterion of productivity towards broader viewpoints. This article focuses on the feasibility of agri-environmental indicators that are aimed to be used for international comparisons. Indicators of two widely known international organizations, OECD and the Commission of European Communities, were evaluated from the viewpoint of national case study. There exist already plenty of methodology to describe agri-environmental development, which mean that future decision-makers will be better informed about the changes of agricultural systems. Data sets are, however, heterogeneous, which needs be carefully acknowledged by the users. Moreover, characteristic feature of agri-environmental indicators is, that they are producing information in a given problem structuring. Therefore, they are unable to recognize the specific properties of each case study. They are providing relevant statistics, but are still missing for the framework, which would open the meaning of numbers and show the relevance of notices within the particular case study.
Aerial sketch-map surveys and systematic forest field inventories may be used separately or in combination to indicate the status of regional forest health. During recent decades, aerially conducted sketch-maps of forest damage and forest inventories have been used to assess oak (Quercus spp) forest health across a 24-state region spanning the northern U.S. In order to more fully inform the monitoring of oak forest health and integrate these independent datasets, the effect of the quality, timing, and repeated sampling of aerial data on correlations with field-based oak forest assessments was assessed. Study results indicated that aerial damage surveys were weakly correlated with indicators of oak forest sustainability (e.g., oak seedlings and saplings), but more highly correlated with overstory attributes such as tree mortality and standing dead. The highest correlations between aerial damage surveys and oak mortality/standing dead were found when the time between the aerial survey and subsequent forest inventory was 4–6 years. Aerial surveys may have their greatest efficacy in supplementing field inventories of oak forest health when they are conducted in a high quality manner with bi-annual or longer remeasurement periods (due to rare pest damage events).
Riparian monitoring is a key aspect of sustainable resource management and is mandated by US federal law for federal land management agencies. However, it is an endeavor hampered by rising manpower costs and time-consuming travel and methods. These limitations tend to reduce sampling intensity per reach of stream and limit monitoring to the larger waterways of management units—limitations that reduce the accuracy of inferences derived from resulting data with consequential reductions in the effectiveness of landscape-level resource management. We tested the utility of low-altitude, high-resolution, intermittent aerial digital imagery for relatively inexpensive, high-intensity sampling in a watershed inhabited by the Lahonton Cutthroat trout, a species listed as threatened under provisions of the US Endangered Species Act. Measurements gleaned from the aerial imagery included late-summer open water width, number and location of late-summer dry channels, widths of riparian areas and willow coverage. All measurements were georeferenced to allow spatial data display. Riparian proper functioning condition (PFC) was assessed from the imagery by a USDI, Bureau of Land Management team. These assessments were compared to similar on-the-ground assessments made during the preceding year. PFC assessments from aerial photography were made using an average 4 staff hours per stream compared to an estimated 36 staff hours per stream for ground PFC assessments. The two assessment methods yielded roughly comparable results. We conclude that riparian-condition assessments from 2-cm GSD digital aerial imagery allowed increased sample intensity (and thus increased inference accuracy) and that it did so in our study at a cost less than half that of conventional ground-based methods. We recommend the acquisition and analysis of 2-cm GSD digital aerial imagery be further trialed for its utility and cost efficiency in ecological monitoring of riparian systems.
Multimetric indices, such as the Index of Biological Integrity (IBI), are increasingly used by management agencies to determine whether surface water quality is impaired. However, important questions about the variability of these indices have not been thoroughly addressed in the scientific literature. In this study, we used a bootstrap approach to quantify variability associated with fish IBIs developed for streams in two Minnesota river basins. We further placed this variability into a management context by comparing it to impairment thresholds currently used in water quality determinations for Minnesota streams. We found that 95% confidence intervals ranged as high as 40 points for IBIs scored on a 0–100 point scale. However, on average, 90% of IBI scores calculated from bootstrap replicate samples for a given stream site yielded the same impairment status as the original IBI score. We suggest that sampling variability in IBI scores is related to both the number of fish and the number of rare taxa in a field collection. A comparison of the effects of different scoring methods on IBI variability indicates that a continuous scoring method may reduce the amount of bias in IBI scores.
There are many fruit trees that could be integrated into dryland farming systems in Sub-Saharan Africa to support income and nutritional security. Fruit contains almost all known vitamins and many essential minerals. Five important fruit species that are cross-regional include: Adansonia digitata, Tamarindus indica, Zizyphus mauritiana, Sclerocarya birrea, and Mangifera indica. While these species are well integrated in the Sahel region, besides mango, they are generally absent from smallholder farms in East and Central Africa. Fruits of the species in this region are mostly harvested unsustainably from the wild communal areas. Unlike the situation in the neighboring Southern Africa region, where S. birrea is utilized extensively in the wine industry, there is virtually no use for the tree in this region, largely because of limited knowledge. Z. mauritiana use is also limited because of low quality germplasm—the hard stone clings to the flesh. An analytical framework based on five factors (site requirements, genetic variability, propagation methods, nutritional properties and utilization, and commercial potential) is used to compare knowledge status and gaps on the species in the region. While this analysis reveals the existence of considerable knowledge between and within the species, lack of improved germplasm and markets emerge as two key constraints limiting their conservation through on-farm planting. Key research and development needs identified are: (a) fostering cross-collaboration and knowledge exchange with other regions where the species are fairly well utilized, and (b) developing criteria and indicators for monitoring impacts and increased investments on the “Big Five” on livelihood of dryland communities and on biodiversity conservation.
The Environmental Protection Agency’s Office of Research and Development (ORD) has prepared technical guidelines to evaluate the suitability of ecological indicators for monitoring programs. The guidelines were adopted by ORD to provide a consistent framework for indicator review, comparison and selection, and to provide direction for research on indicator development. The guidelines were organized within four evaluation phases: (1) conceptual relevance; (2) feasibility of implementation; (3) response variability; (4) interpretation and utility. Three example indicators were analyzed to illustrate the use of the guidelines in an evaluation. The examples included a direct chemical measurement (dissolved oxygen concentration), an estuarine benthic community index, and a stream fish community index of biotic integrity. Comparison of the three examples revealed differences in approach, style and types of information used to address each guideline. The Evaluation Guidelines were intended to be flexible within a consistent framework and the various strategies used in the examples demonstrate that the process can be useful for a wide variety of indicators and program objectives.
The role of life cycle analysis (LCA) in identifying and measuring the environmental impact of extended supply chains, i.e., chains involving both forward and reverse activities, is very important. Particularly, in the case of alternative supply chain management policies or scenarios, life cycle analysis may significantly help to quantify the environmental result of these alternatives for the purpose of comparison and decision making. It is debatable, however, whether such comparison is always possible. Indeed, life cycle analysis has often raised discussion and disagreements, especially regarding the stage of Impact Assessment (valuation), and, until now, there is no generally accepted framework of analysis. In this paper, different models are used in order to extend the usability of the Environmental Design of Industrial Products method of Impact Assessment. Furthermore, research results that are produced by applying different methods of Impact Assessment are examined in the cases of the recovery and disposal chains of lead–acid batteries.
In the last decade efforts have been carried out by the scientific community aimed at building integrated frameworks to support the decision-making process when sustainability issues are addressed. This paper proposes a further advancement in integrated assessment procedures by setting up an operational multi-scale and transparent framework, which comprises the assessment of European regions in terms of sustainability, and the identification of the impact that policy options might have on the sustainability of these regions. The framework is designed for use in ex ante sustainability impact assessment of policy scenarios on multifunctionality of land use and integrates economic, environmental and social issues across a variety of sectors (agriculture, forestry, transport, tourism and energy). The proposed method provides a conceptual framework applicable at different scales (European, regional), and takes into account the great variability of European regions. The described methodology is based on linear additive models to weight and aggregate selected indicators to a set of land use functions identified to describe the goods and services provided by the different land uses that summarise the most relevant economic, environmental and social issues of a region. The framework is designed to allow the evaluation of impacts at an international scale (e.g. the European Union), or on selected regions.
Benthic infaunal communities are frequently used to assess aquatic environmental condition, but interpretation of benthic data is often subjective and based on best professional judgment. Here, we examine the repeatability of such assessments by providing species-abundance data from 35 sites to 9 independent benthic experts who ranked the sites from best to worst condition. Their site rankings were highly correlated, with an average correlation coefficient of 0.91. The experts also evaluated the sites in terms of four condition categories: (1) unaffected, (2) marginal deviation from reference, (3) affected, or (4) severely affected. At least two-thirds of the experts agreed on site categorization for 94% of the samples and they disagreed by more than one category for less than 1% of the assessment pairs. The experts identified seven parameters used in making their assessments, with four of those parameters (dominance by tolerant taxa, presence of sensitive taxa, species richness, and total abundance) used by all of the experts. Most of the disagreements in site categorization were due to philosophical rather than technical differences, such as whether the presence of invasive species indicates a degraded community. Indices are increasingly being used as an alternative to best professional judgment for assessing benthic condition, but there have been inconsistencies in how sites are selected for validating such indices; the level of agreement found among experts in this study suggests that consensus expert opinion can be a viable benchmark for such evaluations.
Agri-environmental measures are among the most important instruments for the promotion of environmentally adapted agricultural land use. While their pertinence in Europe has been increasing for some years, evaluations of these measures have shown that their design is still lacking in both effectiveness and efficiency. This paper describes the derivation of indicator plant species that make it possible to implement result-oriented remuneration schemes in the grassland sector. In many ways, result-oriented agri-environmental schemes can be expected to prove superior to the measure-oriented schemes which are currently most widely used.It is demonstrated how a checklist of indicator species can be derived by using expert knowledge and statistical crosschecks with a database of pre-existing vegetation samples. These species are indicators for conservationally relevant, agriculturally usable grassland on moderately dry to moderately wet sites. The qualities that make a site eligible for remuneration are defined by societal demand as expressed through political objectives and guidelines. One of the challenges in deriving an indicator checklist was to represent quality through species that not only satisfy scientific criteria like validity, but are also operational within remuneration programmes. For example, operational indicator species have to be easily identifiable. The checklist of indicator species for result-oriented remuneration in the Land Brandenburg presented here covers the entire spectrum of site conditions and all types of usable grassland in Brandenburg.
A large number of indicators have been developed, in order to assess agricultural sustainability. However, there is no unified theoretical basis for the creation of a scientifically substantiated system of indicators and especially for data collection, analysis, scale and final goal. This paper proposes a methodological approach to assess and to compare the sustainability level of agricultural plant production systems on regional scale combining the three pillars of sustainability environment, economy and society. The combination of 21 individual indicators expressed a unique indicator was realized using the Multiattribute Value Theory (MAVT). The proposed methodology was testified on two geographical regions in Greece, through an empirical study, utilizing questionnaires completed during interviews with farm managers. The questionnaire was designed to gather data on current agricultural practices applied in each particular region and was separated into three broad groups of questions concerning (a) crop management practices, (b) economic performance and (c) social characteristics of each farm. The results of our study demonstrate the overall status of the studied regions, regarding their level of agricultural sustainability. Finally, findings related to the acceptability of the proposed methodological framework were discussed.
During the last decades, agricultural intensification has modified the hydrology of Mediterranean wetlands, as has occurred in the Mar Menor coastal lagoon (SE Spain). Salt-steppe dominated wetlands, characteristic of transitional areas surrounding this lagoon and rich in biodiversity values, are threatened by changes in their water regime originated by land-use changes in the watershed. Traditional dryland cultures have also been replaced by irrigated ones. We assess the direct and indirect changes induced by agriculture on a terrestrial vertebrate community (steppe birds) especially sensitive to these ecosystem changes. This is made on the basis of several surveys of terrestrial birds (excluding aerial feeders and raptors) carried out between 1984 and 2008 in a representative wetland of the lagoon's continental margin (Marina del Carmolí). The changes in this bird assemblage reflect the hydrological modifications induced by agriculture at the watershed scale, which have significant effects on the relative representation of wetland habitats. Bird metrics and indices (species abundance, taxonomic composition, conservation value) describe these community changes as the combination of early declines in some species and families, and transient or late increases in other. In the long term, the family Alaudidae (and particularly species like Melanocorypha calandra) have lost importance to the benefit of Turdidae and Fringillidae. The area of salt-steppe explains a large part of the variation in the abundance of Alaudidae, while most variation of Turdidae and Fringillidae respond to the area of saltmarsh. Some Alaudidae seem to take advantage of the intermediate stages of saltmarsh expansion (Calandrella rufescens), or from the marginal irrigated crops fringing the wetland (Calandrella brachydactyla) that could compensate the loss of original agricultural habitats. Habitat changes in the wetland have occurred in three differentiated stages, and modify the steppe bird community towards a more heterogeneous assemblage including scrubland and palustrine species. Among three indices of ornithological value, only that based on the EU Bird's Directive Annex I species was negatively affected, but since the wetland has been designated a Specially Protected Area under this regulation, this represents a management failure. There exists some chance, however, to manage peripheral cropland in favour of biodiversity. The importance of monitoring in conservation evaluation and management is also stressed, since the terrestrial bird community of this wetland has not been regularly surveyed. In fact, its evaluation against the Bird's Directive criteria was made in a period of quick departure from the original, good ecological state of the wetland.
Large-scale patterns of benthic diatom assemblages were analyzed in an agricultural basin, the Guadiana River. The distribution patterns of epilithic diatom assemblages were analyzed at different spatial scales: the whole watershed, the upper calcareous subcatchment and the mid-lower siliceous subcatchment. At the whole watershed scale, two major ecological gradients were revealed. The first one summarized the diatom distribution throughout a nutrient concentration gradient, while the second gradient was related to the geological structure of the watershed. Variance partitioning allowed the effects of the different sets of environmental parameters related to every CCA gradient to be separated. Analyzing the subcatchment gradients with partial CCA allowed us to define specific key factors that affect diatom species composition. Although water chemistry consistently played the most important role in structuring diatom assemblages in the Guadiana, spatial factors such as altitude or geographic location also explained some variation in diatom distribution.
Land evaluation is sensitive to the effects of variability of ecologically complex phenomena. A probability map incorporating some of these phenomena is proposed to account for local uncertainty of areas affected by soil degradation in the Apennines of south Italy. To be useful, a method for assessing soil degradation should integrate several kinds of data. We present here an overview of the geostatistical approach to solving this problem: non-linear estimation. The following factors have been considered: the soil erosion by water (geomorphologic indicator), the station aridity (bioclimate indicator), and top-soil depth (pedologic indicator). We convert the continuous data values of each variable at each location using a binary variable indicator transform based on critical thresholds. The indicator transform values for individual variables are then integrated to form multiple variable indicator transform (MVIT) to evaluate the degree of soil degradation. Areas suited to soil degradation maps delineated by geographical information system (GIS), showed that the joint probabilities of meeting specific criteria indicator Kriging were influenced by the critical threshold values used to transform each individual variable and the method of integration. So, the understanding of soil vulnerability to degradation is increased to providing a way to classify degraded regions. On the basis of this information different land uses strategies could be identified to develop sustainable assessment models of soils. For example, many countries of these disadvantaged areas, should have agro-forestation programmes that increase the heterogeneity in vegetation cover contrasting hydrological properties, thus promoting a self-regulating system for runoff and erosional soil degradation control.
Two management systems (conventional vs. organic) in a 3-years crop rotation (pea–durum wheat–tomato) were compared after 4 years in order to assess soil carbon (C) changes in a short-term period. Biochemical properties of soil, such as microbial biomass C and N (MBC and MBN), microbial respiration, N mineralization, dehydrogenase, chitinase, acid–phosphatase, arylsulfatase and β-glucosidase activities, were chosen as indicators of soil organic matter biochemical alteration. The main questions addressed in this study were (1) do soil biochemical properties discriminate between organic and conventional management systems in a short-term period? (2) Which biochemical indicator is more effective in predicting soil organic C accumulation in organically managed agricultural soils?A general increase of hydrolytic enzymes activities has been observed in soil under organic management. MBC, MBN and the MBC/TOC ratio (qmic) increased in organic soil under pea (100%, 50% and 100%, respectively) and durum wheat (55%, 28% and 42%, respectively), while the basal respiration per unit of microbial biomass (qCO2) decreased (48% and 40% under pea and durum wheat, respectively). Moreover, the specific activity of β-glucosidase was significantly lower under organic management of pea and durum wheat and was positively correlated with qCO2, suggesting a lower maintenance energy requirement of the microbial community.Soil microbial biomass and enzymatic activities were successfully used to detect short-term changes in soil and, taking into account its role in soil functioning, β-glucosidase resulted the most suitable indicator to predict organic C accumulation in soil under organic management in a Mediterranean environment.
Connectivity is a key concept of landscape ecology as it relates to flows and movements of organisms as driven by landscape structure. More and more aspects of landscape heterogeneity are considered in measuring connectivity, as the diversity of crops in agricultural landscapes. In this paper, we explored the value of considering changes and cumulated effects of connectivity over time. As an example, we analysed connectivity among patches influenced by maize over 7 years in an agricultural landscape in Brittany, France.Clear temporal patterns appeared: maize is concentrated in certain parts of the landscape, but over the period the whole area, 70% of the landscape, used for maize was connected. Instead of discrete patches, maize may produce large clusters allowing movement from patch to patch from year to year. This reinforces the importance of understanding land use allocation rules within farms and landscapes to evaluate the ecological effects of agriculture.
Conflicts between changing landscapes and static nature protection concepts were addressed as an example of the agricultural landscape of SW Norway. We aimed to deduce indicators for spatio-temporal landscape changes to draw scenarios for future protection perspectives of a RAMSAR and nature reserve. To estimate the variability of bird diversity, changes in vegetation patterns were analysed to predict bird occurrence. We obtained a differentiated analysis of present landscape dynamics by measuring landscape structure, vegetation, hydrology and nutrient concentration. Multivariate statistics were used to extract the main driving forces for changes in vegetation patterns out of a complex landscape ecological data set. Subsequently, we compared the measured data with those of past landscape stages to determine landscape changes and their mechanisms at different spatio-temporal scales. Ecological process indicators (EPI) were derived, and three different indicator constellations were used for scenario descriptions. These scenarios were chosen as to the current assumptions of typical contrasting nature protection strategies. Concluding, we used EPIs to evaluate nature protection aims and to assess scenarios of changing landscapes. This approach will be transferable to other examples of nature protection conflicts in the agricultural landscape in general.
The relationships between, and usefulness of, three different analysis methods: (1) economic cost and return estimation (CAR), (2) ecological footprint (EF) and (3) emergy analysis (EA) in assessing economic viability, ecological carrying capacity and sustainability in tropical crop production was the focus for this study. The analyses were conducted on six agricultural crop production systems in Nicaragua: common bean (Phaseolus vulgaris L.), tomato (Lycopersicum esculentum L. Mill), cabbage (Brassica oleraceae L. var. capitata), maize (Zea mays L.), pineapple (Ananas comosus L. Merr.) and coffee (Coffea arabica L.). The economic indices studied were revenues and profitability. The ecological footprint indices were ecological footprint per hectare of crop (EFcrop), ecological footprint per 1000 USD revenues (EFrev) and ecological footprint per gigacalorie of food energy produced (EFGcal). The emergy analysis indices used were emergy-based profitability (EAprof) and emergy-based ecological footprint (EAEF). The study indicated that cabbage and tomato were the most profitable crops, both in economic and emergy terms, and that coffee was the least profitable crop to grow. On the other hand, beans, coffee and maize were most sustainable when sustainability was measured as ecological carrying capacity, assessed by EF or emergy-based EF, while cabbage and tomato were the least sustainable. Moreover, maize turned out to be the crop with the lowest area demand per production of gigacalorie. Profitability assessed in economic terms or in relation to emergy use (EAprof) or to ecological footprint showed similar patterns and gave the same rankings between the crops. However, profitability assessed by CAR was higher than when assessed by EAprof, due to the fact that no environmental appropriation is included in the CAR. Area appropriation assessed with emergy or with ordinary ecological footprint also resulted in mainly the same rankings between the crops, while the actual size of the areas was at most 10 times larger when assessed in emergy than with plain ecological footprint. Our results add to the body of knowledge on the poor coherence between economic profitability and ecological sustainability. However, we argue that these evaluations may be used as methods for quantitatively assessing different production systems, leading to indices weighting together economic and environmental aspects that may be used to make decisions.
In recent years the objectives of agricultural policy have shifted from a principal focus on production and income towards agriculture's provision of public goods summarized by the term ‘multifunctionality’. Agricultural sector models, which are important tools for policy advice, need to be adjusted in order to maintain their relevance and reliability in accordance with policy changes. This paper investigates the strengths and limitations of incorporating multifunctionality indicators in the agricultural sector model Common Agricultural Policy Regional Impact Analysis (CAPRI) by reviewing the existing literature and incorporating such indicators in the model. Multifunctionality indicators are developed and implemented for four selected aspects of multifunctionality: food security, landscape, environmental concerns and rural viability. By running different policy reform scenarios, it is shown that indicators closely related to the underlying economic variables of the sector model may provide useful to describe the effects of policy reforms on agriculture's multifunctionality. However, these indicators do not completely cover the selected aspects of multifunctionality. In order to yield a broader coverage, this paper proposes to strengthen interdisciplinary research by linking agricultural sector models with other model systems like farm-based economical–ecological models, regional economic models or landscape information systems.
Selecting meaningful metrics to describe landscapes is difficult due to our limited understanding of the links between landscape pattern and ecological process, the numerous indices available and the interaction between the spatial characteristics of the system and metric behaviour. We used an exploratory approach (factor and cluster analysis) for the selection of small sets of landscape descriptors. Twenty-five agricultural landscapes located across temperate Europe were classified using coarse (two and three classes), intermediate (14 classes) and fine (47 classes) scales of thematic resolution. We used statistical analyses to identify which landscape metrics were most useful for distinguishing between different landscapes at each of these scales of thematic resolution. We examined which aspects of spatial pattern were described by the selected metrics and compared our selection with metrics chosen in previous studies. Many of our landscape descriptors were common to earlier investigations but we found that the suitability of the indicators were dependent upon thematic resolution. At coarse thematic scales metrics describing the grain and area occupied by the largest patch (dominance metrics) were suitable to distinguish between landscapes, whereas shape, configuration and diversity indices were more useful at finer scales. At intermediate scales metrics that represent all of these components of landscape pattern were appropriate as landscape descriptors. We anticipate that these results will enable a more informed selection of metrics based on an improved knowledge of the effects of thematic resolution.
Agro-ecological indicators are simple conceptual models to carry out agro-environmental assessments. Their use requires data that need to be obtained at low cost, frequently avoiding direct measurements. The quality of input data thus may limit the usefulness of the indicators. One source of uncertainty is the spatial interpolation of inputs, used to provide indicator values throughout an area. This paper explores the uncertainty of the inputs, and its effect on the output of one indicator, the phosphorus indicator (IP). The indicator evaluates the appropriateness of phosphorus (P) use by farmers, assigning bad scores to over- and under-fertilization. We evaluated its use for P management in the Sud Milano Agricultural Park (northern Italy). We used data contained in a large database of soil and farm properties as well as crop management information at the cadastral parcel level to calculate IP values. The uncertainty of a single input variable (extractable soil P) was tested to quantify the corresponding uncertainty of the indicator. The results show that the variability of IP is high and within 80% of the analyzed area excessive applications of P fertilizers are made, in particular in animal farms. In most cases, uncertainty is not relevant, as it is either very low, or (if high) it is related to extremely low indicator values: in these cases, the assessment of P management is unaffected by the uncertainty of the indicator. The results show that in this area P fertilizers should be applied at lower doses, or not applied at all. An extension service might help farmers with fertilizer management, reducing resource use, environmental pollution and costs. This study shows that uncertainty analysis is a crucial component of environmental assessments, and that the importance of uncertain input data needs to be evaluated on a case-by-case basis.
A holistic stochastic dynamic model was developed by focusing on the interactions between conceptually isolated key-components, such as local passerine guilds and changes in habitat conditions, in Mediterranean agroecosystems of the “Terra Quente Transmontana region” (north-eastern Portugal). The ecological integrity of the typical patchwork of this region, with respect to land use, can be partly assessed by the observation of the occurrence of passerine guilds. These important indicators and state variables are the underlying database of our model. This model aimed the prediction of the ecological changes which can be expected when olive orchards are being intensified. The model proposed was preceded by a conventional multivariate statistical procedure (stepwise multiple regression analysis) performed to discriminate the significant relationships between guild richness and environmental variables. Since this statistical analysis is static, the dataset recorded from the field included true gradients of habitat changes. The model parameters were estimated from the results of the stochastic treatment and from regional data regarding tendencies within the use of land. A period of 50 years was considered. The final model provided some basis to analyse the responses of passerine guilds to the environmental scenarios that will characterize the new agroecosystems of the region. The model simulations were incorporated into a Geographical Information System (GIS) approach. The results of the simulation revealed a structural drift within the different guild richness in response to the expected gradient of habitat changes. The possible local extinction of several species within the less well-represented guilds, such as the steppe passerine species, may be associated with a predictable reduction in ecological integrity of the typical agroecosystems. Therefore, a new structure of the passerine communities indicates that future agroecosystems will diverge from the initial or actual ecological state.
Criteria and indicators (C&I) have emerged as a powerful tool in implementing sustainable forest management. In a relatively short period, around 150 countries have adopted C&I. Some processes have used C&I in forest management and produced progress reports. Six of the seven thematic areas common to all processes are also being used as a basis for reporting progress towards sustainable forest management [e.g., the Food and Agriculture Organization of the United Nations (FAO) in its Global Forest Resource Assessment 2005]. However, there are significant problems in the wider application of C&I. A number of countries are not using C&I at all, and in some countries where they are being used, it is not done in an effective manner. Areas that need improvement in order to promote the use of C&I include: (1) strengthening concepts and definitions; (2) rationalising criteria and indicators; (3) further research on indicators; and (4) utilising C&I in more effective ways. The future development of C&I must be based on an active link between research effort and operational needs in order to prevent a waste of resources and effort. Some of the research undertaken to date has led to the adoption of innovative approaches to optimise resource use and simplify application. This paper identifies areas needing more research and draws from ongoing work to show where progress is being made.
This biomonitoring study was aimed at providing an overall assessment of nitrogen oxides (NOX) and tropospheric ozone (O3) in the Grenoble area (Isère, France). Two bioindicators, lichens and tobacco plants, were used to estimate, respectively, the spatial distribution of NOX and O3. The following methodological approaches were adopted: bioaccumulation of nitrogen in the lichen Physcia adscendens, bioindication of ozone as shown by visible injury to tobacco plants (cv. Bel W3), and biomonitoring at the lichen community level (IAP). Complementary biomonitoring maps, the first based on nitrogen concentrations of lichens and the second based on tobacco leaf injuries, were highly comparable with results obtained from physico-chemical analyses. Multivariate analyses (Canonical Correspondance Analysis) were used to determine the relationships between levels of atmospheric NO2 and O3 and the lichen communities (IAP). A lichen sensitivity scale to NO2 and O3 was attempted for 43 epiphytic species, from which it was possible to define five clusters according to their indifference, sensitivity or resistance to NO2 and O3.